- sherpa.ui.notice_id(ids, lo=None, hi=None, **kwargs)
Include data from the fit for a data set.
Select one or more ranges of data to include by filtering on the independent axis value. The filter is applied to the given data set, or data sets.
Changed in version 4.15.0: The change in the filter is now reported for the dataset.
Changed in version 4.14.0: Integrated data sets - so Data1DInt and DataPHA when using energy or wavelengths - now ensure that the
hiargument is exclusive and better handling of the
loargument when it matches a bin edge. This can result in the same filter selecting a smaller number of bins than in earlier versions of Sherpa.
ids (int or str, or array of int or str) – The data set, or sets, to use.
lo (number or str, optional) – The lower bound of the filter (when a number) or a string expression listing ranges in the form
a:b, with multiple ranges allowed, where the ranges are separated by a
,. The term
:bmeans include everything up to
b(an exclusive limit for integrated datasets), and
a:means include everything that is higher than, or equal to,
hi (number, optional) – The upper bound of the filter when
lois not a string.
bkg_id (int or str, optional) – The filter will be applied to the associated background component of the data set if
bkg_idis set. Only PHA data sets support this option; if not given, then the filter is applied to all background components as well as the source data.
Exclude data from the fit for a data set.
Exclude a spatial region from an image.
Include data in the fit.
Show any filters applied to a data set.
The order of
noticecalls is important.
The units used depend on the
analysissetting of the data set, if appropriate.
To filter a 2D data set by a shape use
The report of the change in the filter expression can be controlled with the
SherpaVerbositycontext manager, as shown in the examples below.
Include all data points with an X value (the independent axis) between 12 and 18 for data set 1:
>>> notice_id(1, 12, 18) dataset 1: 10:30 -> 15:20 x
Include the range 0.5 to 7, for data sets 1, 2, and 3 (the screen output will depend on the existing data and filters applied to them):
>>> notice_id([1, 2, 3], 0.5, 7) dataset 1: 0.00146:14.9504 -> 0.4818:9.0374 Energy (keV) dataset 2: 0.00146:14.9504 -> 0.4964:13.6072 Energy (keV) dataset 3: 0.00146:14.9504 -> 0.4234:9.3878 Energy (keV)
Apply the filter 0.5 to 2 and 2.2 to 7 to the data sets “core” and “jet”, and hide the screen output:
>>> from sherpa.utils.logging import SherpaVerbosity >>> with SherpaVerbsity("WARN"): ... notice_id(["core", "jet"], "0.5:2, 2.2:7") ...